geological model
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Geophysics ◽  
2022 ◽  
pp. 1-48
Author(s):  
Hamed Heidari ◽  
Thomas Mejer Hansen ◽  
Hamed Amini ◽  
Mohammad Emami Niri ◽  
Rasmus Bødker Madsen ◽  
...  

We use a sampling-based Markov chain Monte Carlo method to invert seismic data directly for porosity and quantify its uncertainty distribution in a hard-rock carbonate reservoir in Southwest Iran. The noise that remains on seismic data after the processing flow is correlated with the bandwidth in the range of the seismic wavelet. Hence, to account for the inherent correlated nature of the band-limited seismic noise in the probabilistic inversion of real seismic data, we assume the estimated seismic wavelet as a suitable proxy for capturing the coupling of noise samples. In contrast to the common approach of inserting a delta function on the main diagonal of the covariance matrix, we insert the seismic wavelet on its main diagonal. We also calibrate an empirical and a semi-empirical inclusion-based rock-physics model to characterize the rock-frame elastic moduli via a lithology constrained fitting of the parameters of these models, i.e. the critical porosity and the pore aspect ratio. These calibrated rock-physics models are embedded in the inversion procedure to link petrophysical and elastic properties. In addition, we obtain the pointwise critical porosity and pore aspect ratio, which can potentially facilitate the interpretation of the reservoir for further studies. The inversion results are evaluated by comparing with porosity logs and an existing geological model (porosity model) constructed through a geostatistical simulation approach. We assess the consistency of the geological model through a geomodel-to-seismic modeling approach. The results confirm the performance of the probabilistic inversion in resolving some thin layers and reconstructing the observed seismic data. We present the applicability of the proposed sampling-based approach to invert 3D seismic data for estimating the porosity distribution and its associated uncertainty for four subzones of the reservoir. The porosity time maps and the facies probabilities obtained via porosity cut-offs indicate the relative quality of the reservoir’s subzones.


2022 ◽  
Vol 9 ◽  
Author(s):  
Yonghui Huang ◽  
Yuanzhi Cheng ◽  
Lu Ren ◽  
Fei Tian ◽  
Sheng Pan ◽  
...  

Assessment of available geothermal resources in the deep oil field is important to the synergy exploitation of oil and geothermal resources. A revised volumetric approach is proposed in this work for evaluating deep geothermal potential in an active oil field by integrating a 3D geological model into a hydrothermal (HT)-coupled numerical model. Based on the analysis of the geological data and geothermal conditions, a 3D geological model is established with respect to the study area, which is discretized into grids or elements represented in the geological model. An HT-coupled numerical model was applied based on the static geological model to approximate the natural-state model of the geothermal reservoir, where the thermal distribution information can be extracted. Then the geothermal resource in each small grid element is calculated using a volumetric method, and the overall geothermal resource of the reservoirs can be obtained by making an integration over each element of the geological model. A further parametric study is carried out to investigate the influence of oil and gas saturations on the overall heat resources. The 3D geological model can provide detailed information on the reservoir volume, while the HT natural-state numerical model addressed the temperature distribution in the reservoir by taking into account complex geological structures and contrast heterogeneity. Therefore, integrating the 3D geological modeling and HT numerical model into the geothermal resource assessment improved its accuracy and helped to identify the distribution map of the available geothermal resources, which indicate optimal locations for further development and utilization of the geothermal resources. The Caofeidian new town Jidong oil field serves as an example to depict the calculation workflow. The simulation results demonstrate in the Caofeidian new town geothermal reservoir that the total amount of geothermal resources, using the proposed calculation method, is found to be 1.23e+18 J, and the total geothermal fluid volume is 8.97e+8 m3. Moreover, this approach clearly identifies the regions with the highest potential for geothermal resources. We believe this approach provides an alternative method for geothermal potential assessment in oil fields, which can be also applied globally.


Water ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 75
Author(s):  
Jixiang Zhu ◽  
Yan Lu ◽  
Guanghui Zhang ◽  
Xiaoyuan Zhou ◽  
Guangjun Ji

Accurately depicting the spatial structure characteristics of Quaternary loose sedimentary strata is not only of great significance for the research of Quaternary geological evolution, but also for the analysis of spatial variation characteristics of the inner hydrogeological and engineering geological attributes of the strata. In this study, an approach for constructing a 3D geological model of Quaternary loose sedimentary strata is proposed based on global stratigraphical discrete points. The approach obtains the discrete control point set of each stratum by using limited borehole data for interpolation and encryption, and the contact relationships and intersection modes of adjacent strata can be determined via the analysis of stratigraphic sequence; finally, taking these as the professional basis, the construction of the 3D geological model of Quaternary loose sedimentary strata can be carried out. This application can not only accurately describe the three-dimensional spatial distribution characteristics of the Quaternary loose sedimentary strata, it can also be used to perform a layered simulation of the spatial variation characteristics of the inner geological properties of the Quaternary loose sedimentary strata, such as lithology, porosity, and water content, by taking the three-dimensional spatial framework of each stratum as the simulation boundary. Finally, this study takes the citizen center of Xiong’an new area as an example in order to verify the reliability and advancement of the 3D geological modeling scheme.


2022 ◽  
Vol 2148 (1) ◽  
pp. 012007
Author(s):  
Mingwen Chi

Abstract In this paper, the technology of profile generation based on 3D model is studied. The main steps are as follows: (1) the location where the profile needs to be generated in 3D model design; (2) Using 3D data cutting technology to realize the generation of geological lines in profile; (3) Read the basic exploration data related to profile position in the database; (4) According to the data generated in the first three steps, the cross-section is automatically drawn after data coordinate transformation. The above method can quickly generate the geological profile of any location according to the 3D geological model, which is helpful for geological analysis and provides reference data for engineering design.


2021 ◽  
Vol 54 (2F) ◽  
pp. 22-35
Author(s):  
Haider Mahmood ◽  
Omar Al-Fatlawi

The paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applied based on sensitivity and uncertainty of five variables to determine an accurate estimation of stock-tank oil initially in place of the reservoir. The oil-water contact appeared to be the major uncertain parameter for stock-tank oil initially in place estimation because the available geological and field data was not enough to demonstrate it confidently, and only 13% of the total wells have penetrated the water zone in the Mishrif formation. The results of all scenarios indicate that the reservoir has huge stock-tank oil initially in place. The importance of developing this oilfield is validated by its very high stock-tank oil. This is where the value of this study becomes obvious.


2021 ◽  
Vol 44 (4) ◽  
pp. 417-432
Author(s):  
Lujun Lin ◽  
Hui Chen ◽  
Zhenshan Pang ◽  
Zhizhong Cheng ◽  
Jianling Xue ◽  
...  

The prediction theory and methodology of ore prospecting were developed from an in-depth study of 129 typical deposits in China. It has been verified to be an effective method that is particularly suitable for the initial ore prospecting. In this method, the internal and external factors of metallogenesis are combined together to construct a geological model of prospecting prediction, which consists of metallogenic geological body, metallogenic structure, metallogenic structural plane and metallogenic characteristics. The Huili area is located in the western margin of the Yangtze Plate, where the regional metallogenic geological conditions are superior, and a series of unique iron-copper deposits were formed. In recent years, great breakthroughs and progress have been made in the deep and peripheral areas of the Huili copper orefield. Herein, we take the Huili copper orefield as a typical example to illustrate the specific application of this method in deep ore prospecting of hydrothermal deposits. The metallogenic geological body is the ore-hosting volcanic rocks (albitite in the Hekou Group), and the main metallogenic structure and structural planes are interfaces between basic (intermediate) volcanic rocks and sedimentary rocks and the possible volcanic vent. Combined with the summary of metallogenic characteristics, we constructed a geological model for ore prospecting in the Huili copper orefield.


Author(s):  
V.V. Kasatkin ◽  
K.V. Svetlov ◽  
K.F. Miropoltsev ◽  
Yu.I. Shilov

The paper analyzes one of the most important and difficult stages of constructing a geological model of the Beregovoye field when calculating hydrocarbon reserves – the correlation of the productive strata. It considers the productive strata of the Pokur formation of continental origin, analyzes the conditions of sedimentation, recommends the main correlation benchmarks and examines their characteristic features and inherent patterns.


2021 ◽  
Vol 6 (4) ◽  
pp. 32-42
Author(s):  
Dmitriy V. Kozikov ◽  
Mikhail A. Vasiliev ◽  
Konstantin V. Zverev ◽  
Andrei N. Lanin ◽  
Shafkat A. Nigamatov ◽  
...  

Background. The article considers the results of updating the geological model of the khamakinskii horizon reservoirs of the Chayandinskoe oid and gas field. The main aim is project the production of the oil rims and form a positive business case of the project. Materials and methods. Conceptual sedimentary model bases on the core of the 14 wells. Updating of the petrophysical model is the key to identify post-sedimentary transformations (like anhydritization and halitization) and the opportunity to correct the permeability trend. The tectonic pattern of the horizon based on the interpretation of 3D seismic data. There are two groups of faults were identified: certain and possible. Neural networks algorithm uses for a creating the predictive maps of anhydritization, which are used in the geological model. Results. Estuary sands influenced by fluvial and tidal processes dominate the khamakinskii horizon. The reservoir is irregular vertically: at the base of the horizon, there are sandstones of the delta front and there are alluvial valley with fluvial channels in the middle and upper parts. Eustary sands eroded by incised valleys (alluvial channels). According to the core and thin section analysis, the main uncertainty is sedimentary transformations of reservoir. It affects the net thickness and then the volume of oil in productive wells. 3D geological model includes the trends of anhydritization and halitization over the area, which makes it possible to obtain a more accurate production forecast. Conclusion. As part of the probability estimate of oil reserves, the main geological parameters that affect the volume of reserves were identified. Pilot project is planning to remove geological and technical uncertainties.


2021 ◽  
Author(s):  
Zhouji Liang ◽  
Florian Wellmann

Geological modeling has been widely adopted to investigate underground geometries. However, modeling processes inevitably have uncertainties due to scarcity of data, measurement errors, and simplification of modeling methods. Recent developments in geomodeling methods have introduced a Bayesian framework to constrain the model uncertainties by considering additional geophysical data into the modeling procedure. Markov chain Monte Carlo (MCMC) methods are normally used as tools to solve the Bayesian inference problem. To achieve a more efficient posterior exploration, advances inMCMC methods utilize derivative information. Hence, we introduce an approach to efficiently evaluate second-order derivatives in geological modeling and introduce a Hessian-informed MCMC method, the generalized preconditioned Crank-Nicolson (gpCN), as a tool to solve the 3D model-based gravity Bayesian inversion problem. The result is compared with two other widely applied MCMC methods, random walk Metropolis-Hasting and Hamiltonian Monte Carlo, on a synthetic three-layer geological model. Our experiment demonstrates that superior performance is achieved by the gpCN, which has the potential to be generalized to more complex models.


2021 ◽  
Author(s):  
Alexey Vasilievich Timonov ◽  
Rinat Alfredovich Khabibullin ◽  
Nikolay Sergeevich Gurbatov ◽  
Arturas Rimo Shabonas ◽  
Alexey Vladimirovich Zhuchkov

Abstract Geosteering is an important area and its quality determines the efficiency of formation drilling by horizontal wells, which directly affects the project NPV. This paper presents the automated geosteering optimization platform which is based on live well data. The platform implements online corrections of the geological model and forecasts well performance from the target reservoir. The system prepares recommendations of the best reservoir production interval and the direction for horizontal well placements based on reservoir performance analytics. This paper describes the stages of developing a comprehensive system using machine-learning methods, which allows multivariate calculations to refine and predict the geological model. Based on the calculations, a search for the optimal location of a horizontal well to maximize production is carried out. The approach realized in the work takes into account many factors (some specific features of geological structure, history of field development, wells interference, etc.) and can offer optimum horizontal well placement options without performing full-scale or sector hydrodynamic simulation. Machine learning methods (based on decision trees and neural networks) and target function optimization methods are used for geological model refinement and forecasting as well as for selection of optimum interval of well placement. As the result of researches we have developed the complex system including modules of data verification and preprocessing, automatic inter-well correlation, optimization and target interval selection. The system was tested while drilling hydrocarbons in the Western Siberian fields, where the developed approach showed efficiency.


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